code: def __call__(self, data):
      if isinstance(data, (list, tuple)):
          data = asseries(data)
      elif isinstance(data, pd.Series):
          data = from_pandas_series(data)
      elif isinstance(data, pd.DataFrame):
          data = from_pandas_df(data)
  
      if self.prefix is not None:
          if isinstance(self.prefix, list):
              if self.columns is not None:
                  encoding_col_num = len(self.columns)
              else:
                  encoding_col_num = 0
                  for dtype in data.dtypes.values:
                      if dtype.kind in _encoding_dtype_kind:
                          encoding_col_num += 1
              prefix_num = len(self.prefix)
              if prefix_num != encoding_col_num:
                  raise ValueError(
                      f"Length of 'prefix' ({prefix_num}) did not match "
                      + f"the length of the columns being encoded ({encoding_col_num})"
                  )
          elif isinstance(self.prefix, dict):
              if self.columns is not None:
                  encoding_col_num = len(self.columns)
                  prefix_num = len(self.prefix)
                  if prefix_num != encoding_col_num:
                      raise ValueError(
                          f"Length of 'prefix' ({prefix_num}) did not match "
                          + f"the length of the columns being encoded ({encoding_col_num})"
                      )
                  columns = self.prefix.keys()
                  for columns_columnname, prefix_columnname in zip(
                      columns, list(self.columns)
                  ):
                      if columns_columnname != prefix_columnname:
                          raise KeyError(f"{columns_columnname}")
              else:
                  self.columns = list(self.prefix.keys())
              # Convert prefix from dict to list, to simplify tile work
              self.prefix = list(self.prefix.values())
  
      return self.new_dataframe(
          [data],
          shape=(np.nan, np.nan),
          dtypes=None,
          index_value=data.index_value,
          columns_value=None,
      )
  
file_path: mars/mars/dataframe/base/get_dummies.py
imports: import numpy
  import pandas
  from ...core import OutputType, recursive_tile
  from ...serialization.serializables import StringField, BoolField, AnyField, ListField
  from ..core import SERIES_TYPE
  from ..datasource.dataframe import from_pandas
  from ..datasource.series import from_pandas
  from ..initializer import Series
  from ..operands import DataFrameOperand, DataFrameOperandMixin
  from ..reduction.unique import unique
  from ..utils import gen_unknown_index_value
label_desc: Use image node_id 4 for calling the DataFrameGetDummies obj's underlying member method code with example usage: obj.__call__(data) and returns: self